Doyeon Ha¹, Donghyo Kim¹, Inhae Kim², Youngchul Oh¹, JungHo Kong¹, Seong Kyu Han¹ and Sanguk Kim^1,3,4,*

¹Department of Life Sciences, Pohang University of Science and Technology, Pohang, Korea, ²ImmunoBiome Inc., Pohang, Korea, ³Graduate School of Artificial Intelligence, Pohang University of Science and Technology, Pohang, Korea and ⁴Institute of Convergence Research and Education in Advanced Technology, Yonsei University, Seoul, Korea

^*Corresponding author.

Mouse models have been engineered to reveal the biological mechanisms of human diseases based on an assumption. The assumption is that orthologous genes underlie conserved phenotypes across species. However, genetically modified mouse orthologs of human genes do not often recapitulate human disease phenotypes which might be due to the molecular evolution of phenotypic differences across species from the time of the last common ancestor. Here, we systematically investigated the evolutionary divergence of regulatory relationships between transcription factors (TFs) and target genes in functional modules, and found that the rewiring of gene regulatory networks (GRNs) contributes to the phenotypic discrepancies that occur between humans and mice. We confirmed that the rewired regulatory networks of orthologous genes contain a higher proportion of species-specific regulatory elements. Additionally, we verified that the divergence of target gene expression levels, which was triggered by network rewiring, could lead to phenotypic differences. Taken together, a careful consideration of evolutionary divergence in regulatory networks could be a novel strategy to understand the failure or success of mouse models to mimic human diseases. To help interpret mouse phenotypes in human disease studies, we provide quantitative comparisons of gene expression profiles on our website (http://sbi.postech.ac.kr/w/RN).